• KDI Journal of Economic Policy
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• v.44 no.3
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• pp.1-26
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• 2022

This paper analyzes the effects of the cut in the legal maximum interest rate (from 27.4% to 24%) that occurred in February of 2018 on loan interest rates, the default rates, and the loan approval rate of borrowers in the non-banking sector. We use the difference-in-difference identification strategy to estimate the effect of the cut in the legal maximum interest rate using micro-level data from a major credit-rating company. The legal maximum rate cut significantly lowers the loan interest rate and default rate of low-credit borrowers (i.e., high-credit-risk borrowers) in the non-banking sector. However, this effect is limited to borrowers who have not been excluded from the market despite the legal maximum interest rate cut. The loan approval rate of low-credit borrowers decreased significantly after the legal maximum interest rate cut. Meanwhile, the loan approval rate of high-credit and medium-credit (i.e., low credit risk and medium credit risk) borrowers increased. This implies that financial institutions in the non-banking sector should reduce the loan supply to low-credit borrowers who are no longer profitable while increasing the loan supply to high- and medium-credit borrowers.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.12
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• pp.3768-3774
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• 2009

This paper explored how soft information and hard information were used when SBC(Small Business Corporation, Korea) reviewed government loan applications. The data set is made up of financial and non-financial data of small-business firms since 2004. A non-financial data set is considered as soft information. Relative importance of three kinds information such as credit information, soft information, financial information is compared with each other by using the logit model. As a result, credit information is most critical to the loan approval, and then soft information follows, lastly financial information has the smallest effect on the loan approval. This is because the credit information is made up of the non-linear combination of soft information and financial information. When the relative importance of soft information and financial information is considered, soft information is relatively more critical to the loan approval then financial information. This is because financial ratios provided by small-business firms are not reliable enough.

• Korean Journal of Construction Engineering and Management
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• v.20 no.5
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• pp.137-148
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• 2019

Many construction developers have tried to develop the international PPP (Public-Private Partnership) projects but frequently failed to gain loan investor approval from loan investor. Many of these failures were caused by the risk attitude gaps among project stakeholder. This study aims to compare the risk attitude between the construction investor and loan investor. This study investigated how much differently 21 construction investors and 21 loan investor recognize the risk magnitude corresponding to the same three risk status of 27 risk factors. Construction investors show a more risk-seeking attitude than loan investor in 58 of 81 risk status. Loan investors show a more risk-averse attitude than construction investors in 9 risk factors. These results will contribute to developing the successful PPP project by reducing the risk perception gap between construction investors and loan investors.

• Journal of Intelligence and Information Systems
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• v.13 no.2
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• pp.15-26
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• 2007

In this study, a SOHO (Small Office Home Office) bankruptcy prediction model is proposed using Modified Bagging Predictors which is modification of traditional Bagging Predictors. There have been several studies on bankruptcy prediction for large and middle size companies. However, little studies have been done for SOHOs. In commercial banks, loan approval processes for SOHOs are usually less structured than those for large and middle size companies, and largely depend on partial information such as credit scores. In this study, we use a real SOHO loan approval data set of a Korean bank. First, decision tree induction techniques and artificial neural networks are applied to the data set, and the results are not satisfactory. Bagging Predictors which has been not previously applied for bankruptcy prediction and Modified Bagging Predictors which is proposed in this paper are applied to the data set. The experimental results show that Modified Bagging Predictors provides better performance than decision tree inductions techniques, artificial neural networks, and Bagging Predictors.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.9
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• pp.229-239
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• 2020

This paper examines the impact of gender on access to debt finance among Vietnamese enterprises. The paper investigates data and variables retrieved from the World Bank Enterprise Survey dataset using five Probit models. The regression results suggest that there exist more unfavourable debt financing conditions for women-led firms (WLF), measured as a lower probability of having loan applications fully approved. Firm's age, working sector, and perception of access to finance as a difficulty are found to have explanatory power on the discrimination. More importantly, the perception of debt finance as a difficulty or firms' level of confidence significantly explains the variance of the dependent variable of probability of loan approval, or gender effect would be more pronounced if the firm already has a low level of confidence. The paper also contributes in testing for the gender effect on Vietnamese enterprises from different sectors and scale, unlike other prior research papers focusing on specific sectors and/or small and medium enterprises only. The findings are highly useful for Vietnamese credit institutions to set out a specific business policy to attract more WLFs and help promoting gender equality in the working environment, especially in debt financing, which is often neglected in existing regulation and policy frameworks.

• Asia pacific journal of information systems
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• v.5 no.1
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• pp.52-85
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• 1995

This paper develops a new approach to dealing with qualitative reasoning processes involved in managerial decisions, drawing upon choice strategies that have been developed within the general framework of multi-criteria decision making. Issues such as choices under uncertainty and preference formulation are addressed. An MCDM DSS intended to assist in high-level management decisions must focus on helping the decision maker to properly define the problem by providing a structure to it and to dynamically evaluate the alternative courses of action. A conceptual architecture is developed and presented to propose a general model for designing decision support systems specifically designed to assist in MCDM in a managerial context. A commercial loan approval judgment case is described to illustrate the real-world situation where decisions are made under fuzziness and usually require a high degree of intuition and subjective judgment. Development of a prototype system intended to partially represent application of the architecture is described.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.10
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• pp.129-138
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• 2021

Several studies have revealed that information on borrower characteristics plays an important factor in approving their credit requests. Though the extent to which such characteritics are also applicable to the case of fintech lending remain uncertain. The aim of this study is, thus, to investigate the determinant factors that influence MSEs in obtaining credit through fintech lending. Here, we emphasize virtual trust in fintech lending encompasing the dimension of social network, economic attributes, and risk perception based on several indicators that are used as proxies. Primary data used in the study was gathered from an online survey to the respondents of MSEs in Java. The result of the study indicates that determinants of MSEs in obtaining credit from lender through fintech lending are statistically influenced by internet usage activities, borrowing history, loan utilization, annuity payment system, completeness of credit requirement documents and compatibility of loan size with the business need. These factors have a significant effect on credit approval because they can generate virtual trust of fintech lender to MSEs as potential borrowers. It concludes that the probability of obtaining fintech loans in accordance with their expectations are influenced by the dimensions of social network, economic attributes and risk perception.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.2
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• pp.151-156
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• 2020

Small and medium enterprises (SMEs) play a very important role in developing countries. In Vietnam, SMEs operating in the field of handicrafts, besides contributing to the economy, also tasked to maintain and develop traditional handicrafts. However, accessing loans from banks of SMEs faces many difficulties. This study explores the determinants of bank lending decision for SMEs, particular, in traditional handicrafts business. Using dataset based on a survey conducted in Binh Duong province, Vietnam, we investigated to what determinant effects for loan approval. The analytical methods used include descriptive statistics for overall assessment, principal component analysis and regression to examine determinants of lending decisions. The results indicate that company's collateral was the most positive determinant to bank lending decision, follow by company's business plan. The role of company's leader is very important for banks considers to approve credit because company's leaders experience and relationship with stakeholders as well as banks have positive relations with bank's lending decision. Agreed with previous studies, the company's financial statement and company's credit history with banks are also significant determinants for lending decision. Whereas, the business environment seam unaffected lending decision as their relations is not significant..

• The Korean Journal of Air & Space Law and Policy
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• v.32 no.2
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• pp.129-153
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• 2017

Fair Competition policy in aviation field has been discussed since open skies policy began in 1970s. This issue has been also the main topic in the ICAO's Worldwide Air Transport Conference, the Air Transport Symposium, etc. ICAO defines competition as the existent or potential rivalry between two or more operators, carriers or groups, striving for advantages in the same market based on different prices, qualities and services. In a broader sense, the definition includes more various meanings; reasonable, fair, effective, and unrestricted competitions. Nowadays, competition laws and regulations to air transportation have been applied more frequently and the issues varies from antitrust immunity, mergers and alliances, abuse of dominant positions, capacity dumping and predatory pricing, sales and marketing, to airport charges and fees, state aid and loan guarantees. Now, the competition among the airlines or nations in aviation industry is changing to cooperation level. A lot of airlines try to survive by various cooperation methods. Therefore the policy of Korean aviation industry should be developed, taking so-called "the viewpoint of national aviation industry ecosystem" into consideration and Korean government should prepare a policy of fair competition to cope with it. First, in the process of open skies policy with neighboring countries such as China, Japan and the Middle East, it is necessary to apply the fair competition act and prepare laws and regulations to implement it. Second, the standards of effective ownership and control of air transportation business should be reviewed. Third, in preparation for aviation agreements and liberalization, the Korean aviation industry needs to study and review competition and cooperation issues through the analysis of strict aviation market structure for airlines and airport operations. Fourth, it is necessary to create a fair air transportation environment for the development of air transportation and competitiveness through preemptive policies such as the approval of mergers, acquisitions, JV and the ripple effects analysis.